package com.zhengjiang.stream;

import lombok.Data;

import java.util.*;
import java.util.stream.Collectors;
import java.util.stream.Stream;

/**
 * @author zhengjiang
 * @version 1.0.0
 * @description 20 个实例玩转 Java 8 Stream https://mp.weixin.qq.com/s/rVPNwBzDlgUDqsLJl7g9qg
 * @date 2021/7/31
 **/
public class StreamDemo {

    static List<Person> personList = new ArrayList<>();

    static {
        personList.add(new Person("Tom", 9500, 20, "male", "New York"));
        personList.add(new Person("Jack", 7000, 30, "male", "Washington"));
        personList.add(new Person("Lily", 7000, 35, "female", "Washington"));
        personList.add(new Person("Anni", 8200, 40, "female", "New York"));
        personList.add(new Person("Owen", 9500, 50, "male", "New York"));
        personList.add(new Person("Alisa", 7900, 60, "female", "New York"));
    }

    public static void main(String[] args) {
//        test1();
//        test2();
//        test3();
//        test4();
//        test5();
//        test6();
//        test7();
//        test8();
//        test9();
//        test10();
//        test11();
        test12();
    }



    //Stream的创建
    private static void test1() {
        //1、通过 java.util.Collection.stream() 方法用集合创建流
        List<String> list = Arrays.asList("a","b","c");
        //创建顺序流
        Stream<String> stream = list.stream();
        stream.forEach(System.out::print);
        System.out.println();
        //创建并行流
        Stream<String> parallelStream = list.parallelStream();
        printStream(parallelStream);
        System.out.println();
        //2、使用java.util.Arrays.stream(T[] array)方法用数组创建流
        Stream<Integer> integerStream1 = Arrays.stream(new Integer[]{1, 2, 3, 4, 5});
        printStream(integerStream1);
        System.out.println();
        //3、使用Stream的静态方法：of()、iterate()、generate()
        Stream<Integer> integerStream2 = Stream.of(1, 2, 3, 4, 5);
        printStream(integerStream2);
        System.out.println();
        Stream<Integer> iterateStream3 = Stream.iterate(0, (x) -> x + 2).limit(4);
        printStream(iterateStream3);
        System.out.println();
        Stream<Double> stream3 = Stream.generate(Math::random).limit(3);
        printStream(stream3);
    }

    // 遍历/匹配（foreach/find/match）
    private static void test2(){
        List<Integer> list = Arrays.asList(1,4,6,7,8,10);
        Stream<Integer> integerStream1 = list.stream().filter(x -> x > 6);
        integerStream1.forEach(System.out::println);

        Optional<Integer> first1 = list.stream().filter(x -> x < 1).findFirst();
        first1.ifPresent(System.out::println);

        Optional<Integer> optional1 = list.stream().filter(x -> x > 5).findFirst();
        optional1.ifPresent(x-> System.out.println( x * 5));

        list.parallelStream().filter(x -> x > 5).findAny().ifPresent(System.out::println);

        boolean b = list.stream().anyMatch(x -> x > 6);
        System.out.println(b);

        Stream<Person> personStream = personList.stream().filter(x -> x.getSalary() > 8000);
        personStream.map(Person::getName).forEach(System.out::println);
    }


    //聚合（max/min/count)
    private static void test3(){
        Optional<Person> max = personList.stream().max(Comparator.comparingInt(Person::getSalary));
        if (max.isPresent()){
            Person person = max.get();
            System.out.println(person.getName());
        }

        Optional<Person> min = personList.stream().min(Comparator.comparingInt(Person::getSalary));
        if (min.isPresent()){
            Person person = min.get();
            System.out.println(person.getName());
        }

        long count = personList.stream().filter(x -> x.getSalary() > 7000).count();
        System.out.println(count);

    }

    // 映射(map/flatMap)
    private static void test4(){
        String[] strArr = { "abcd", "bcdd", "defde", "fTr" };
        List<String> strList = Arrays.stream(strArr).map(String::toUpperCase).collect(Collectors.toList());

        List<Integer> intList = Arrays.asList(1, 3, 5, 7, 9, 11);
        List<Integer> intListNew = intList.stream().map(x -> x + 3).collect(Collectors.toList());

        System.out.println("每个元素大写：" + strList);
        System.out.println("每个元素+3：" + intListNew);

        List<String> list = Arrays.asList("m,k,l,a", "1,3,5,7");
        List<String> listNew = list.stream().flatMap(s -> {
            // 将每个元素转换成一个stream
            String[] split = s.split(",");
            Stream<String> s2 = Arrays.stream(split);
            return s2;
        }).collect(Collectors.toList());

        System.out.println("处理前的集合：" + list);
        System.out.println("处理后的集合：" + listNew);
    }

    //归约(reduce) : 也称缩减，顾名思义，是把一个流缩减成一个值，能实现对集合求和、求乘积和求最值操作。
    private static void test5(){
        //求Integer集合的元素之和、乘积和最大值
        List<Integer> list = Arrays.asList(1, 3, 2, 8, 11, 4);
        // 求和方式1
        Optional<Integer> sum = list.stream().reduce((x, y) -> x + y);
        // 求和方式2
        Optional<Integer> sum2 = list.stream().reduce(Integer::sum);
        // 求和方式3
        Integer sum3 = list.stream().reduce(0, Integer::sum);

        // 求乘积
        Optional<Integer> product = list.stream().reduce((x, y) -> x * y);

        // 求最大值方式1
        Optional<Integer> max = list.stream().reduce((x, y) -> x > y ? x : y);
        // 求最大值写法2
        Integer max2 = list.stream().reduce(1, Integer::max);

        System.out.println("list求和：" + sum.get() + "," + sum2.get() + "," + sum3);
        System.out.println("list求积：" + product.get());
        System.out.println("list求最大值：" + max.get() + "," + max2);

        //求所有员工的工资之和和最高工资。
        // 求工资之和方式1：
        Optional<Integer> sumSalary = personList.stream().map(Person::getSalary).reduce(Integer::sum);
        // 求工资之和方式2：
        Integer sumSalary2 = personList.stream().reduce(0, (s, p) -> s += p.getSalary(),
                (s1, s2) -> s1 + s2);
        // 求工资之和方式3：
        Integer sumSalary3 = personList.stream().reduce(0, (s, p) -> s += p.getSalary(), Integer::sum);

        // 求最高工资方式1：
        Integer maxSalary = personList.stream().reduce(0, (m, p) -> m > p.getSalary() ? m : p.getSalary(),
                Integer::max);
        // 求最高工资方式2：
        Integer maxSalary2 = personList.stream().reduce(0, (m, p) -> m > p.getSalary() ? m : p.getSalary(),
                (m1, m2) -> m1 > m2 ? m1 : m2);

        System.out.println("工资之和：" + sumSalary.get() + "," + sumSalary2 + "," + sumSalary3);
        System.out.println("最高工资：" + maxSalary + "," + maxSalary2);
    }

    //归集(toList/toSet/toMap)
    private static void test6(){
        List<Integer> list = Arrays.asList(1, 6, 3, 4, 6, 7, 9, 6, 20);
        List<Integer> listNew = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toList());
        Set<Integer> set = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toSet());

        Map<?, Person> map = personList.stream().filter(p -> p.getSalary() > 8000)
                .collect(Collectors.toMap(Person::getName, p -> p));
        System.out.println("toList:" + listNew);
        System.out.println("toSet:" + set);
        System.out.println("toMap:" + map);
    }

    //统计(count/averaging)
    /**
     * Collectors提供了一系列用于数据统计的静态方法：
     *
     * 计数：count
     *
     * 平均值：averagingInt、averagingLong、averagingDouble
     *
     * 最值：maxBy、minBy
     *
     * 求和：summingInt、summingLong、summingDouble
     *
     * 统计以上所有：summarizingInt、summarizingLong、summarizingDouble
     */
    private static void test7(){
        // 求总数
        Long count = personList.stream().collect(Collectors.counting());
        // 求平均工资
        Double average = personList.stream().collect(Collectors.averagingDouble(Person::getSalary));
        // 求最高工资
        Optional<Integer> max = personList.stream().map(Person::getSalary).collect(Collectors.maxBy(Integer::compare));
        // 求工资之和
        Integer sum = personList.stream().collect(Collectors.summingInt(Person::getSalary));
        // 一次性统计所有信息
        DoubleSummaryStatistics collect = personList.stream().collect(Collectors.summarizingDouble(Person::getSalary));

        System.out.println("员工总数：" + count);
        System.out.println("员工平均工资：" + average);
        System.out.println("员工工资总和：" + sum);
        System.out.println("员工工资所有统计：" + collect);
    }

    //分组(partitioningBy/groupingBy)
    /**
     * 分区：将stream按条件分为两个Map，比如员工按薪资是否高于8000分为两部分。
     *
     * 分组：将集合分为多个Map，比如员工按性别分组。有单级分组和多级分组。
     */
    private static void test8(){
        // 将员工按薪资是否高于8000分组
        Map<Boolean, List<Person>> part = personList.stream().collect(Collectors.partitioningBy(x -> x.getSalary() > 8000));
        // 将员工按性别分组
        Map<String, List<Person>> group = personList.stream().collect(Collectors.groupingBy(Person::getSex));
        // 将员工先按性别分组，再按地区分组
        Map<String, Map<String, List<Person>>> group2 = personList.stream().collect(Collectors.groupingBy(Person::getSex, Collectors.groupingBy(Person::getArea)));
        System.out.println("员工按薪资是否大于8000分组情况：" + part);
        System.out.println("员工按性别分组情况：" + group);
        System.out.println("员工按性别、地区：" + group2);
    }

    // 接合(joining)
    //joining可以将stream中的元素用特定的连接符（没有的话，则直接连接）连接成一个字符串。
    private static void test9(){
        String names = personList.stream().map(p -> p.getName()).collect(Collectors.joining(","));
        System.out.println("所有员工的姓名：" + names);
        List<String> list = Arrays.asList("A", "B", "C");
        String string = list.stream().collect(Collectors.joining("-"));
        System.out.println("拼接后的字符串：" + string);
    }

    // 归约(reducing)
    //Collectors类提供的reducing方法，相比于stream本身的reduce方法，增加了对自定义归约的支持。
    private static void test10(){
        // 每个员工减去起征点后的薪资之和（这个例子并不严谨，但一时没想到好的例子）
        Integer sum = personList.stream().collect(Collectors.reducing(0, Person::getSalary, (i, j) -> (i + j - 5000)));
        System.out.println("员工扣税薪资总和：" + sum);

        // stream的reduce
        Optional<Integer> sum2 = personList.stream().map(x -> x.getSalary() - 5000).reduce(Integer::sum);
        System.out.println("员工薪资总和：" + sum2.get());
    }


    //排序(sorted)

    /**
     * sorted，中间操作。有两种排序：
     *
     * sorted()：自然排序，流中元素需实现Comparable接口
     *
     * sorted(Comparator com)：Comparator排序器自定义排序
     */
    private static void test11(){
        // 按工资升序排序（自然排序）
        List<String> newList = personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName)
                .collect(Collectors.toList());
        // 按工资倒序排序
        List<String> newList2 = personList.stream().sorted(Comparator.comparing(Person::getSalary).reversed())
                .map(Person::getName).collect(Collectors.toList());
        // 先按工资再按年龄升序排序
        List<String> newList3 = personList.stream()
                .sorted(Comparator.comparing(Person::getSalary).thenComparing(Person::getAge)).map(Person::getName)
                .collect(Collectors.toList());
        // 先按工资再按年龄自定义排序（降序）
        List<String> newList4 = personList.stream().sorted((p1, p2) -> {
            if (p1.getSalary() == p2.getSalary()) {
                return p2.getAge() - p1.getAge();
            } else {
                return p2.getSalary() - p1.getSalary();
            }
        }).map(Person::getName).collect(Collectors.toList());

        System.out.println("按工资升序排序：" + newList);
        System.out.println("按工资降序排序：" + newList2);
        System.out.println("先按工资再按年龄升序排序：" + newList3);
        System.out.println("先按工资再按年龄自定义降序排序：" + newList4);
    }

    //提取/组合
    //流也可以进行合并、去重、限制、跳过等操作
    private static void test12(){
        String[] arr1 = { "a", "b", "c", "d" };
        String[] arr2 = { "d", "e", "f", "g" };

        Stream<String> stream1 = Stream.of(arr1);
        Stream<String> stream2 = Stream.of(arr2);
        // concat:合并两个流 distinct：去重
        List<String> newList = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
        // limit：限制从流中获得前n个数据
        List<Integer> collect = Stream.iterate(1, x -> x + 2).limit(10).collect(Collectors.toList());
        // skip：跳过前n个数据
        List<Integer> collect2 = Stream.iterate(1, x -> x + 2).skip(1).limit(5).collect(Collectors.toList());

        System.out.println("流合并：" + newList);
        System.out.println("limit：" + collect);
        System.out.println("skip：" + collect2);
    }


    private static <T> void printStream(Stream<T> stream){
        stream.forEach(System.out::print);
    }
}

@Data
class Person{
    private String name;  // 姓名
    private int salary; // 薪资
    private int age; // 年龄
    private String sex; //性别
    private String area;  // 地区

    // 构造方法
    public Person(String name, int salary, int age, String sex, String area) {
        this.name = name;
        this.salary = salary;
        this.age = age;
        this.sex = sex;
        this.area = area;
    }


}
